Evidence map›Paper›PMID 35309226›Full record

ArticleFrontiers in public health2022

Which Contributes to Clinical Performance: Academic Output or Person-Environment Fit?

Minye Dong, Yuyin Xiao, Chenshu Shi, Wu Zeng, Fan Wu, Guohong Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Minye DongSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuyin XiaoSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chenshu ShiCenter for Health Technology Assessment, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai, China.
Wu ZengDepartment of International Health, Georgetown University, Washington, DC, United States.
Fan WuShanghai Medical College, Fudan University, Shanghai, China.
Guohong LiSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The measures put in place by health authorities to ensure the professionalism of doctors are important. Hospitals in China have included academic outputs in the promotion criteria to incentive medical clinicians to engage in scientific research so that to improve job performance (JP). However, such practice disproportionally focuses on academic outputs but ignores the force of needs fulfilled brought by intrinsic incentive. This study aims to discuss the realistic problem regarding the promotion mechanism and the potential drivers to clinical JP. Methods: This study was based on multi-source data collection on clinical performance from electric medical record (EMR), person-environment (P-E) fit from the survey, and academic output from personnel files of ward clinicians ( Results: Clinicians who were promoted were more productive in producing academic outputs than those who were not ( Conclusion: This study shows that P-E fit plays a more important role in facilitating clinical performance than academic performance and highlights the importance of intrinsic motivation of clinicians in achieving clinical performance.

Indexed as

PhysiciansChinaHumansMotivationSurveys and Questionnairesacademic outputcareer progressionclinical performanceperformance assessmentperson-environment fitpromotionqualification certification

Identifiers

PMID35309226
PMCPMC8931592

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.